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eess.SP updates on arXiv.org

ECG-biometrics-bench: A Unified Framework for Reproducible Benchmarking of ECG Biometrics Physiology-Aware Masked Cross-Modal Reconstruction for Biosignal Representation Learning Towards Improving Speaker Distance Estimation through Generative Impulse Response Augmentation Federated Learning with Hypergradient-based Online Update of Aggregation Weights Soft Graph Diffusion Transformer for MIMO Detection SPLICE: Latent Diffusion over JEPA Embeddings for Conformal Time-Series Inpainting Sequential Inference for Gaussian Processes: A Signal Processing Perspective Statistical Channel Fingerprint Construction for Massive MIMO: A Unified Tensor Learning Framework Recent Advances in mm-Wave and Sub-THz/THz Oscillators for FutureG Technologies Cross-Subject Generalization for EEG Decoding: A Survey of Deep Learning Methods Super-resolution Multi-signal Direction-of-Arrival Estimation by Hankel-structured Sensing and Decomposition Hankel and Toeplitz Rank-1 Decomposition of Arbitrary Matrices with Applications to Signal Direction-of-Arrival Estimation Adaptive Transform Coding for Semantic Compression EdgeSpike: Spiking Neural Networks for Low-Power Autonomous Sensing in Edge IoT Architectures Sparse Graph Learning from Sparse Data via Fiedler Number Maximization A Deep Learning Model for Battery State Prediction towards Intelligent Energy Management Transfer Learning for Tonal Noise Prediction in VRF Units Using Thermodynamic and Vibration Signals EVT-Based Generative AI for Tail-Aware Channel Estimation Monitoring exposure-length variations in submarine power cables using distributed fiber-optic sensing BandRouteNet: An Adaptive Band Routing Neural Network for EEG Artifact Removal Phase-Separated Complex Hilbert PCA on Markerless 3D Pose Estimation Data: A Global Phase Network and Its Extension to a Continuous Field on the Body Surface Selective Correlation Based Knowledge Distillation for Ground Reaction Force Estimation Deep Learning-Enabled Dissolved Oxygen Sensing in Biofouling Environments for Ocean Monitoring Speech Enhancement Based on Drifting Models Robust and Clinically Reliable EEG Biomarkers: A Cross Population Framework for Generalizable Parkinson's Disease Detection An AI-Based Supervisory Measurement Integrity Validation Layer for Cyber-Resilient AC/DC Protection in Inverter-Based Microgrids Explainable AI in Speaker Recognition -- Making Latent Representations Understandable Time-Localized Parametric Decomposition of Respiratory Airflow for Sub-Breath Analysis NAKUL-Med: Spectral-Graph State Space Models with Dynamics Kernels for Medical Signals An Algorithm for On-Sensor Agnostic Detection of Changes in Human Activity for Ultra-Low-Power Applications
Design of a Multi-User Wireless Powered Communication Sys...
Omid Rezaei, Maryam Masjedi, Ali Kanaani, Mohammad Mahdi Naghsh, · 2022-12-31 · via eess.SP updates on arXiv.org

In this paper, we optimize a Wireless Powered Communication (WPC) system including multiple pair of users, where transmitters employ single-antenna to transmit their information and power to their receivers with the help of one multiple-antennas Amplify-and-Forward (AF) relay or an active Intelligent Reflecting Surface (IRS). We propose a joint Time Switching (TS) scheme in which transmitters, receivers, and the relay/IRS are either in their energy or information transmission/reception modes. The transmitted multi-carrier unmodulated and modulated waveforms are used for Energy Harvesting (EH) and Information Decoding (ID) modes, respectively. In order to design an optimal fair system, we maximize the minimum rate of all pairs for both relay and IRS systems through a unified framework. This framework allows us to simultaneously design energy waveforms, find optimal relay/IRS amplification/reflection matrices, allocate powers for information waveforms, and allocate time durations for various phases. In addition, we take into account the non-linearity of the EH circuits in our problem. This problem turns out to be non-convex. Thus, we propose an iterative algorithm by using the Minorization-Maximization (MM) technique, which quickly converges to the optimal solution. Numerical examples show that the proposed method improves the performance of the multi-pair WPC relay/IRS system under various setups.